Internet of things applications, security challenges, attacks, intrusion detection, and future visions: A systematic review
N Mishra, S Pandya - IEEE Access, 2021 - ieeexplore.ieee.org
Internet of Things (IoT) technology is prospering and entering every part of our lives, be it
education, home, vehicles, or healthcare. With the increase in the number of connected …
education, home, vehicles, or healthcare. With the increase in the number of connected …
A survey on data-driven network intrusion detection
Data-driven network intrusion detection (NID) has a tendency towards minority attack
classes compared to normal traffic. Many datasets are collected in simulated environments …
classes compared to normal traffic. Many datasets are collected in simulated environments …
Dual-IDS: A bagging-based gradient boosting decision tree model for network anomaly intrusion detection system
The mission of an intrusion detection system (IDS) is to monitor network activities and
assess whether or not they are malevolent. Specifically, anomaly-based IDS can discover …
assess whether or not they are malevolent. Specifically, anomaly-based IDS can discover …
Fast anomaly identification based on multiaspect data streams for intelligent intrusion detection toward secure industry 4.0
Various cyber attacks often occur in logistics network of the Industry 4.0, which poses a
threat to Internet security. Intrusion detection can intelligently detect anomalous activities …
threat to Internet security. Intrusion detection can intelligently detect anomalous activities …
Building an efficient intrusion detection system based on feature selection and ensemble classifier
Y Zhou, G Cheng, S Jiang, M Dai - Computer networks, 2020 - Elsevier
Intrusion detection system (IDS) is one of extensively used techniques in a network topology
to safeguard the integrity and availability of sensitive assets in the protected systems …
to safeguard the integrity and availability of sensitive assets in the protected systems …
Adaptive machine learning based distributed denial-of-services attacks detection and mitigation system for SDN-enabled IoT
The development of smart network infrastructure of the Internet of Things (IoT) faces the
immense threat of sophisticated Distributed Denial-of-Services (DDoS) security attacks. The …
immense threat of sophisticated Distributed Denial-of-Services (DDoS) security attacks. The …
[HTML][HTML] CPS-GUARD: Intrusion detection for cyber-physical systems and IoT devices using outlier-aware deep autoencoders
Abstract Detecting attacks to Cyber-Physical Systems (CPSs) is of utmost importance, due to
their increasingly frequent use in many critical assets. Intrusion detection in CPSs and other …
their increasingly frequent use in many critical assets. Intrusion detection in CPSs and other …
Hybrid approach to intrusion detection in fog-based IoT environments
CA De Souza, CB Westphall, RB Machado… - Computer Networks, 2020 - Elsevier
Abstract In the Internet of Things (IoT) systems, information of various kinds is continuously
captured, processed, and transmitted by systems generally interconnected by the Internet …
captured, processed, and transmitted by systems generally interconnected by the Internet …
Active ensemble learning for knowledge graph error detection
Knowledge graphs (KGs) could effectively integrate a large number of real-world assertions,
and improve the performance of various applications, such as recommendation and search …
and improve the performance of various applications, such as recommendation and search …
A comprehensive review on deep learning algorithms: Security and privacy issues
Abstract Machine Learning (ML) algorithms are used to train the machines to perform
various complicated tasks that begin to modify and improve with experiences. It has become …
various complicated tasks that begin to modify and improve with experiences. It has become …